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A Mobile Field Robot with Vision-Based Detection of Volunteer Potato Plants in a Corn Crop

Published online by Cambridge University Press:  20 January 2017

Frits K. Van Evert ,
Gerie W.A.M. Van Der Heijden ,
Lambertus A.P. Lotz ,
Gerrit Polder ,
Arjan Lamaker ,
Arjan De Jong ,
Marjolijn C. Kuyper ,
Eltje J.K. Groendijk ,
Jacques J. Neeteson  and
Ton Van Der Zalm
Frits K. Van Evert*
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Gerie W.A.M. Van Der Heijden
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Lambertus A.P. Lotz
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Gerrit Polder
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Arjan Lamaker
Affiliation:
Wageningen UR, Wageningen, The Netherlands
Arjan De Jong
Affiliation:
Center for Geo-Information, P.O. Box 47, 6700 AA Wageningen, The Netherlands
Marjolijn C. Kuyper
Affiliation:
Center for Geo-Information, P.O. Box 47, 6700 AA Wageningen, The Netherlands
Eltje J.K. Groendijk
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Jacques J. Neeteson
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
Ton Van Der Zalm
Affiliation:
Plant Research International, P.O. Box 16, 6700 AA Wageningen, The Netherlands
*
Corresponding author's E-mail: frits.vanevert@wur.nl.
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Abstract

Volunteer potato is a perennial weed that is difficult to control in crop rotations. It was our objective to build a small, low-cost robot capable of detecting volunteer potato plants in a cornfield and thus demonstrate the potential for automatic control of this weed. We used an electric toy truck as the basis for our robot. We developed a fast row-recognition algorithm based on the Hough transform and implemented it using a webcam. We developed an algorithm that detects the presence of a potato plant based on a combination of size, shape, and color of the green elements in an image and implemented it using a second webcam. The robot was able to detect potatoes while navigating autonomously through experimental and commercial cornfields. In a first experiment, 319 out of 324 images were correctly classified (98.5%) as showing, or not showing, a potato plant. In a second experiment, 126 out of 141 images were correctly classified (89.4%). Detection of a potato plant resulted in an acoustic signal, but future robots may be fitted with weed control equipment, or they may use a global positioning system to map the presence of weed plants so that regular equipment can be used for control.

Keywords

Corn, Zea mays L, Potato, Solanum tuberosum L.Autonomous navigationautonomous weedingglyphosatemachine-visionsite-specific weed controlDIPlib, Delft image-processing libraryDSP, digital signal processorGPS, global positioning systemJPEG, Joint Photographic Experts GroupNiMh, nickle metal hydridePC, personal computer
Type
Research
Information
Weed Technology , Volume 20 , Issue 4 , December 2006 , pp. 853 - 861
Copyright
Copyright © Weed Science Society of America 

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